Human decision-making often transcends our formal models of
"rationality." Designing intelligent agents that interact
proficiently with people necessitates the modeling of human
behavior and the prediction of their decisions. In this book, we
explore the task of automatically predicting human decision-making
and its use in designing intelligent human-aware automated computer
systems of varying natures-from purely conflicting interaction
settings (e.g., security and games) to fully cooperative
interaction settings (e.g., autonomous driving and personal robotic
assistants). We explore the techniques, algorithms, and empirical
methodologies for meeting the challenges that arise from the above
tasks and illustrate major benefits from the use of these
computational solutions in real-world application domains such as
security, negotiations, argumentative interactions, voting systems,
autonomous driving, and games. The book presents both the
traditional and classical methods as well as the most recent and
cutting edge advances, providing the reader with a panorama of the
challenges and solutions in predicting human decision-making.
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